Manage output files in less-janky fashion.

justfile

@@ -1,11 +1,5 @@
 run *name:
-    python3 ./model.py
+    python3 ./model.py -n "{{ name }}"
-    @if [[ ! -z "{{ name }}" ]]; then \
-        OUT_DIR="output/{{ name }}"; \
-        rm -rf "${OUT_DIR}"; \
-        mkdir -p "${OUT_DIR}"; \
-        mv bitcoin_*.png bitcoin_*.txt "${OUT_DIR}"; \
-    fi
 
 fmt:
     black ./*.py
@@ -14,4 +8,4 @@ lint:
     ruff check ./model.py
 
 clean:
-    rm -f bitcoin_*.png bitcoin_*.txt
+    rm -rf output

model.py

@@ -1,10 +1,58 @@
+import argparse
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
+import os
 import seaborn as sns
+import shutil
 import warnings
 from datetime import timedelta
 from multiprocessing import Pool
+from typing import BinaryIO
+
+
+# Output
+
+
+class Output:
+    """
+    Output ensures result files get written to the right directory.
+
+    Example:
+        output = Output("output", "test-1")
+        with output.create("summary.txt") as f:
+            # path to f is "output/test-1/summary.txt"
+    """
+
+    out_dir: str
+
+    def __init__(self, base_dir: str, name: str):
+        """
+        Initialize the output manager. This will both fully delete any existing
+        output directory, and then create an empty directory for the output.
+
+        Args:
+            base_dir: The root directory for outputs
+            name: The subdir of the root, where the results files go
+        """
+        self.out_dir = os.path.join(base_dir, name)
+        shutil.rmtree(self.out_dir, ignore_errors=True)
+        os.makedirs(self.out_dir)
+
+    def create(self, filename) -> BinaryIO:
+        """
+        Create a new file for writing in the output directory.
+        """
+        full_path = self.named(filename)
+        f = open(full_path, "w")
+        return f
+
+    def named(self, filename) -> str:
+        """
+        Get the full path within the output directory for a named results file.
+        """
+        full_path = os.path.join(self.out_dir, filename)
+        return full_path
 
 
 # Utility functions
@@ -640,7 +688,7 @@ def analyze_bitcoin_prices(csv_path):
 # Main plotting functions
 
 
-def create_plots(df, start=None, end=None, project_days=365):
+def create_plots(df, output: Output, start=None, end=None, project_days=365):
     """
     Create enhanced plots including market maturity visualization.
     """
@@ -832,7 +880,9 @@ def create_plots(df, start=None, end=None, project_days=365):
     # Save the plot
     start_str = start if start else plot_df["Date"].min().strftime("%Y-%m-%d")
     end_str = end if end else plot_df["Date"].max().strftime("%Y-%m-%d")
-    filename = f"bitcoin_analysis_{start_str}_to_{end_str}_with_projections.png"
+    filename = output.named(
+        f"bitcoin_analysis_{start_str}_to_{end_str}_with_projections.png"
+    )
 
     # Use tight_layout with adjusted parameters
     plt.tight_layout(pad=2.0)
@@ -842,7 +892,7 @@ def create_plots(df, start=None, end=None, project_days=365):
     return projections
 
 
-def visualize_cycle_patterns(df, cycle_returns, cycle_volatility):
+def visualize_cycle_patterns(df, output: Output, cycle_returns, cycle_volatility):
     """
     Create enhanced visualization of Bitcoin's behavior across halving cycles.
     """
@@ -1041,12 +1091,17 @@ def visualize_cycle_patterns(df, cycle_returns, cycle_volatility):
     plt.tight_layout()
 
     # Save the plot
-    plt.savefig("bitcoin_cycle_patterns.png", dpi=300, bbox_inches="tight")
+    filename = output.named("bitcoin_cycle_patterns.png")
+    plt.savefig(filename, dpi=300, bbox_inches="tight")
     plt.close()
 
 
 def create_backtest_plot(
-    df, backtest_date="2020-05-11", start_date="2012-11-28", project_days=1650
+    df,
+    output: Output,
+    backtest_date="2020-05-11",
+    start_date="2012-11-28",
+    project_days=1650,
 ):
     """
     Create a plot comparing actual price history against model projections from a historical date.
@@ -1246,7 +1301,9 @@ def create_backtest_plot(
 
     # Adjust layout and save
     plt.tight_layout()
-    filename = f'bitcoin_backtest_{start_date.strftime("%Y%m%d")}_to_{backtest_date.strftime("%Y%m%d")}.png'
+    filename = output.named(
+        f'bitcoin_backtest_{start_date.strftime("%Y%m%d")}_to_{backtest_date.strftime("%Y%m%d")}.png'
+    )
     plt.savefig(filename, dpi=300, bbox_inches="tight")
     plt.close()
 
@@ -1254,11 +1311,11 @@ def create_backtest_plot(
 
 
 def run_projection(args):
-    df, start = args
+    df, start, output = args
-    _ = create_plots(df, start=start, project_days=365 * 4)
+    _ = create_plots(df, output, start=start, project_days=365 * 4)
 
 
-def run_projections(df):
+def run_projections(df, output: Output):
     # Create main projection
     projection_starts = [
         "2011-01-01",
@@ -1268,7 +1325,7 @@ def run_projections(df):
         "2015-01-01",
         "2016-07-09",
     ]
-    args = [(df, start) for start in projection_starts]
+    args = [(df, start, output) for start in projection_starts]
     with Pool() as pool:
         pool.map(run_projection, args)
 
@@ -1281,13 +1338,13 @@ def run_single_backtest(args):
     Args:
         args: tuple of (params dict, DataFrame)
     """
-    params, df = args
+    params, df, output = args
     try:
         # Create a copy of params without the description
         backtest_params = params.copy()
         backtest_params.pop("description", None)
 
-        projections, metrics = create_backtest_plot(df, **backtest_params)
+        projections, metrics = create_backtest_plot(df, output, **backtest_params)
 
         # Ensure metrics has all required keys with default values
         if metrics is None:
@@ -1317,7 +1374,9 @@ def run_single_backtest(args):
         return {"params": params, "error": str(e), "success": False}
 
 
-def run_systematic_backtests(df, validation_years=2, min_training_years=8):
+def run_systematic_backtests(
+    df, output: Output, validation_years=2, min_training_years=8
+):
     """
     Run a comprehensive suite of backtests with consistent validation periods.
     Uses sliding windows for both start and end dates.
@@ -1463,7 +1522,7 @@ def run_systematic_backtests(df, validation_years=2, min_training_years=8):
         print(f"- {period['description']}")
 
     # Create args tuples with params and DataFrame
-    args = [(params, df) for params in unique_periods]
+    args = [(params, df, output) for params in unique_periods]
 
     # Use multiprocessing
     with Pool() as pool:
@@ -1517,7 +1576,7 @@ def run_systematic_backtests(df, validation_years=2, min_training_years=8):
     stress_metrics = calculate_category_metrics(stress_periods_results)
 
     # Write detailed results
-    with open("bitcoin_backtest_results_summary.txt", "w") as f:
+    with output.create("bitcoin_backtest_results_summary.txt") as f:
         f.write("Systematic Backtest Results\n")
         f.write("==========================\n\n")
 
@@ -1601,20 +1660,38 @@ def run_systematic_backtests(df, validation_years=2, min_training_years=8):
     )
 
 
-# if __name__ == "__main__":
+# CLI
-#    analysis, df = analyze_bitcoin_prices("prices.csv")
-#    procs = []
-#
-#    for proc in procs:
-#        proc.join()
-#
 
 
-if __name__ == "__main__":
+def get_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        prog="model",
+        description="Bitcoin price model",
+    )
+    parser.add_argument(
+        "-o",
+        "--output",
+        help="output base directory",
+        default="./output",
+    )
+    parser.add_argument(
+        "-n",
+        "--name",
+        help="subdir of output base directory",
+        default="baseline",
+    )
+    return parser.parse_args()
+
+
+def main():
+    args = get_args()
+    global output
+    output = Output(args.output, args.name)
+
     analysis, df = analyze_bitcoin_prices("prices.csv")
-    run_projections(df)
+    run_projections(df, output)
     normal_metrics, stress_metrics, normal_results, stress_results, failed_tests = (
-        run_systematic_backtests(df)
+        run_systematic_backtests(df, output)
     )
 
     print("\nAggregate Metrics:")
@@ -1631,3 +1708,7 @@ if __name__ == "__main__":
     for test in failed_tests:
         print(f"Period: {test['params']['description']}")
         print(f"Error: {test['error']}\n")
+
+
+if __name__ == "__main__":
+    main()